Machine Learning

Building a Simple Neural Network |  TensorFlow for Hackers (Part II)

In this one, you will build a Neural Network which tries to decide whether or not a student has drinking problem. Will you get good accuracy from the model?

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Machine Learning

Data Imputation using Autoencoders | What to do when data is missing? (Part II)

Let's use a Deep Autoencoder to impute missing categorical data from a dataset describing physical characteristics of mushrooms. How well can we do it? Let's try it with Keras in Python.

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Machine Learning

TensorFlow Basics | TensorFlow for Hackers (Part I)

Learning TensorFlow is easy and fun! Want to learn more about Machine Learning and Deep Learning in a practical and hands-on approach using TensorFlow? Let's start with a simple linear regression.

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Machine Learning

Introduction to Data Imputation | What to do when data is missing? (Part I)

Yes! You've got the coolest dataset on your hard drive. Countless hours of fun are waiting for you. Except, some rows have missing values and your model might not be happy with those. But you have the perfect solution! You can just ignore them (nobody said delete them, right?)! Now, why this might not be the best idea? Let's dig deeper into data imputation using R.

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